コード例 #1
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def LSTM_sequence_classifer_net(feature, num_output_classes, embedding_dim, LSTM_dim, cell_dim):
    embedding_function = embedding(feature, embedding_dim)
    LSTM_function = LSTMP_component_with_self_stabilization(
        embedding_function.output, LSTM_dim, cell_dim)[0]
    thought_vector = sequence.last(LSTM_function)

    return linear_layer(thought_vector, num_output_classes)
コード例 #2
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def LSTM_sequence_classifer_net(input, num_output_classes, embedding_dim, LSTM_dim, cell_dim):
    embedding_function = embedding(input, embedding_dim)
    LSTM_function = LSTMP_component_with_self_stabilization(
        embedding_function.output, LSTM_dim, cell_dim)[0]
    thought_vector = sequence.last(LSTM_function)

    return linear_layer(thought_vector, num_output_classes)
コード例 #3
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ファイル: simplernn.py プロジェクト: w1y2l32009/CNTK 
def LSTM_sequence_classifer_net(input, num_output_classes, embedding_dim,
                                LSTM_dim, cell_dim):
    embedded_inputs = embedding(input, embedding_dim)
    lstm_outputs = simple_lstm(embedded_inputs, LSTM_dim, cell_dim)[0]
    thought_vector = sequence.last(lstm_outputs)
    return linear_layer(thought_vector, num_output_classes)
コード例 #4
0
ファイル: simplernn.py プロジェクト: FDecaYed/CNTK 
def LSTM_sequence_classifer_net(input, num_output_classes, embedding_dim,
                                LSTM_dim, cell_dim):
    embedded_inputs = embedding(input, embedding_dim)
    lstm_outputs = simple_lstm(embedded_inputs, LSTM_dim, cell_dim)[0]
    thought_vector = sequence.last(lstm_outputs)
    return linear_layer(thought_vector, num_output_classes)